Results 51 to 60 of about 4,220,052 (297)
Translating Phrases in Neural Machine Translation [PDF]
Proceedings of the 2017 Conference on Empirical Methods in Natural
Language Processing, 2017 Accepted by EMNLP ...
Deyi Xiong +3 more
openaire +3 more sources
Unsupervised Chunking Based on Graph Propagation from Bilingual Corpus
The Scientific World Journal, 2014 This paper presents a novel approach for unsupervised shallow parsing model trained on the unannotated Chinese text of parallel Chinese-English corpus. In this approach, no information of the Chinese side is applied. The exploitation of graph-based label
Ling Zhu, Derek F. Wong, Lidia S. Chao
doaj +1 more source
Are ambiguous conjunctions problematic for machine translation? [PDF]
, 2019 The translation of ambiguous words still poses challenges for machine translation. In this work, we carry out a systematic quantitative analysis regarding the ability of different machine translation systems to disambiguate the source language ...
Castilho, Sheila, Popović, Maja
core +1 more source
Interactive Machine Translation [PDF]
, 2011 [EN] Achieving high-quality translation between any pair of languages is not possible with the current Machine-Translation (MT) technology a human post-editing of the outputs of the MT system being necessary. Therefore, MT is a suitable area to apply the Interactive Pattern Recognition (IPR) framework and this application has led to what nowadays is ...
Toselli, Alejandro Héctor +5 more
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Improving Neural Machine Translation Models with Monolingual Data [PDF]
Annual Meeting of the Association for Computational Linguistics, 2015 Neural Machine Translation (NMT) has obtained state-of-the art performance for several language pairs, while only using parallel data for training. Target-side monolingual data plays an important role in boosting fluency for phrase-based statistical ...
Rico Sennrich +2 more
semanticscholar +1 more source
Comparative Legilinguistics, 2019 With the advent of the neural paradigm, machine translation has made another leap in quality. As a result, its use by trainee translators has increased considerably, which cannot be disregarded in translation pedagogy.
Wiesmann Eva
doaj +4 more sources
Study on Post-editing for Machine Translation of Railway Engineering Texts [PDF]
SHS Web of Conferences, 2021 With rapid development of China's railways, there are more overseas construction projects and technical exchanges in the field of railway engineering, which have generated widespread demands for translation.
Li Yuting, Lu Xiuying
doaj +1 more source
Neural Machine Translation Advised by Statistical Machine Translation
Proceedings of the AAAI Conference on Artificial Intelligence, 2017 Neural Machine Translation (NMT) is a new approach to machine translation that has made great progress in recent years. However, recent studies show that NMT generally produces fluent but inadequate translations (Tu et al. 2016b; 2016a; He et al. 2016; Tu et al. 2017). This is in contrast to conventional Statistical Machine Translation (
Wang, Xing +5 more
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Challenges in translational machine learning [PDF]
Human Genetics, 2022 AbstractMachine learning (ML) algorithms are increasingly being used to help implement clinical decision support systems. In this new field, we define as “translational machine learning”, joint efforts and strong communication between data scientists and clinicians help to span the gap between ML and its adoption in the clinic.
Artuur Couckuyt +6 more
openaire +3 more sources
Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation [PDF]
Transactions of the Association for Computational Linguistics, 2016 We propose a simple solution to use a single Neural Machine Translation (NMT) model to translate between multiple languages. Our solution requires no changes to the model architecture from a standard NMT system but instead introduces an artificial token ...
Melvin Johnson +11 more
semanticscholar +1 more source